For this data story, I am interested in how Sustainable Development Goals 7 (affordable and clean energy), 12 (responsible consumption and production), and 13 (climate action) differ among countries with varying GDP’s. I will be using these 7 countries to investigating these relationships: the US, Germany, Egypt, India, Brazil, Australia, and Japan.
This data set if provided by the International Renewable Energy Agency (IRENA), an agency driving sustainable energy use world wide and providing data on renewable energy. We will be calling this dataset “energy” and filtering the data to only include the 7 countries of focus, calling that “energy_filtered”.
## Country.area Technology Data.Type Grid.connection
## 1 Australia Total renewable Electricity Generation (GWh) On-grid
## 2 Australia Total renewable Electricity Generation (GWh) On-grid
## 3 Australia Total renewable Electricity Generation (GWh) On-grid
## 4 Australia Total renewable Electricity Generation (GWh) On-grid
## 5 Australia Total renewable Electricity Generation (GWh) On-grid
## 6 Australia Total renewable Electricity Generation (GWh) On-grid
## Year Electricity.statistics
## 1 2000 17590.10
## 2 2001 18162.10
## 3 2002 17874.10
## 4 2003 18619.10
## 5 2004 18683.10
## 6 2005 20103.10
This data set if provided by Gapminder, a foundation that provides data and transparency on human living conditions and global development. We will be calling this dataset “gapminder” and filtering the data to only include the 7 countries of focus, calling that “gapminder_filtered”.
## # A tibble: 6 × 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 Australia Oceania 1952 69.1 8691212 10040.
## 2 Australia Oceania 1957 70.3 9712569 10950.
## 3 Australia Oceania 1962 70.9 10794968 12217.
## 4 Australia Oceania 1967 71.1 11872264 14526.
## 5 Australia Oceania 1972 71.9 13177000 16789.
## 6 Australia Oceania 1977 73.5 14074100 18334.
This data set if provided by the Global Carbon Project. (I wasn’t able to get the link to open, I think because it is blocked on the school wi-fi, but this is what I found). We will be calling this dataset “carbon” and filtering the data to only include the 7 countries of focus, calling that “carbon_filtered”.
## # A tibble: 6 × 79
## country year iso_code population gdp cement_co2 cement_co2_per_capita co2
## <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Austra… 1750 AUS 314500 NA NA NA 0
## 2 Austra… 1751 AUS NA NA NA NA 0
## 3 Austra… 1752 AUS NA NA NA NA 0
## 4 Austra… 1753 AUS NA NA NA NA 0
## 5 Austra… 1754 AUS NA NA NA NA 0
## 6 Austra… 1755 AUS NA NA NA NA 0
## # ℹ 71 more variables: co2_growth_abs <dbl>, co2_growth_prct <dbl>,
## # co2_including_luc <dbl>, co2_including_luc_growth_abs <dbl>,
## # co2_including_luc_growth_prct <dbl>, co2_including_luc_per_capita <dbl>,
## # co2_including_luc_per_gdp <dbl>, co2_including_luc_per_unit_energy <dbl>,
## # co2_per_capita <dbl>, co2_per_gdp <dbl>, co2_per_unit_energy <dbl>,
## # coal_co2 <dbl>, coal_co2_per_capita <dbl>, consumption_co2 <dbl>,
## # consumption_co2_per_capita <dbl>, consumption_co2_per_gdp <dbl>, …
This data set if provided by Our World in Data, an organization that provides data and infomation on global issues such as poverty, hunger, climate change, inequality, etc. We will be calling this dataset “econ” and filtering the data to only include the 7 countries of focus, calling that “econ_filtered”.
## # A tibble: 6 × 4
## country year source cost
## <chr> <dbl> <chr> <dbl>
## 1 Australia 2010 Bioenergy NA
## 2 Australia 2010 Geothermal NA
## 3 Australia 2010 Offshore wind NA
## 4 Australia 2010 Solar photovoltaic 0.424
## 5 Australia 2010 Concentrated solar power NA
## 6 Australia 2010 Hydropower NA
The data that I am using is pulled from the Carbon Emissions dataset, specifically looking at their data collection on…
…between the US, Germany, Egypt, India, Brazil, Australia, and Japan.
First, I am getting an idea of the discrepancies in GDP per capita among these 7 countries included in this analysis. It shows that the US, Australia and Germany tend to have the highest GDP’s per capita while Egypt and India have only had significant increases since the 1960’s.
Then, I wanted to see how these countries differ in their energy use per capita. The countries with the highest GDP’s per capita are showing similarly high energy use while the countries with the lowest GDP’s per capita also have the lowest energy use.
I also wanted to see the impact on temperature change in these countries and see how it compares to the information in the previous figures. The US shows an increase in temperatures much greater than that of the other 6 countries.
I saw that there was data on the CO2 emissions per unit energy and I wanted to see what this looked like in these countries, now keeping in mind their GDP per capita and their energy use per capita. It shows that India, the country with the lowest GDP and energy use per capita, has the highest CO2 emissions per unit of energy of all 7 countries over the past 20 years. Australia, a country with high GDP and energy use per capita, also has high CO2 emissions per unit of energy, even higher than the US. I also found it interesting that Brazil, Germany, and the US have the lowest CO2 emissions per unit of energy but were also the 3 countries with the highest temperature change from CO2. (I couldn’t remember how to re order the countries on the x-axis).
Finally… this one doesn’t look great but I was trying to make it work because I thought these would be cool together. The scales are too different for each so I tried facet wrapping them. It’s hard to compare them but you can still see which ones have positive and negative relationships. India and Brazil, the countries with some of the the lowest GDP and energy use per capita, are the only two that show an increase in temperature change as energy use per capita increases which is not what I would have expected.
| country | gdp_per_cap | energy_per_capita | co2 | temperature_change_from_co2 |
|---|---|---|---|---|
| India | 7349.57 | 7129.11 | 2831.166 | 0.037 |
| Egypt | 12967.95 | 9968.82 | 271.169 | 0.003 |
| Brazil | 15156.04 | 17333.80 | 483.841 | 0.055 |
| Japan | 38196.70 | 40377.67 | 1032.687 | 0.032 |
| Germany | 46495.28 | 40938.07 | 671.472 | 0.042 |
| Australia | 51305.38 | 63452.27 | 384.362 | 0.014 |
| United States | 57075.34 | 78347.91 | 5078.871 | 0.239 |
The wealthiest countries per capita also tend to be the countries that are using the most energy. But interestingly enough, they are not the ones seeing the increases in temperatures as their energy consumption increases. For example, as energy consumption increases in the US, temperature change decreases, as you can see above.
The cost of our consumption is not often manifested in the same places. Countries with enough money to push the problems somewhere else or better financially support relief and preventative measures are also often the ones causing the greatest damage and not facing the hardest consequences.
Sustainable Development Goals 12 is a particularly important goal that bleeds into so many others. If we want to think about energy and our climate crisis, we have to consider what we are consuming and just how many consequences there are that we do not see.